{
  "id": "1911.12663",
  "version": "v1",
  "published": "2019-11-28T12:12:18.000Z",
  "updated": "2019-11-28T12:12:18.000Z",
  "title": "System Identification for Hybrid Systems using Neural Networks",
  "authors": [
    "Mattias Fält",
    "Pontus Giselsson"
  ],
  "categories": [
    "math.OC"
  ],
  "abstract": "With new advances in machine learning and in particular powerful learning libraries, we illustrate some of the new possibilities they enable in terms of nonlinear system identification. For a large class of hybrid systems, we explain how these tools allow for identification of complex dynamics using neural networks. We illustrate the method by examining the performance on a quad-rotor example.",
  "revisions": [
    {
      "version": "v1",
      "updated": "2019-11-28T12:12:18.000Z"
    }
  ],
  "analyses": {
    "keywords": [
      "hybrid systems",
      "neural networks",
      "nonlinear system identification",
      "quad-rotor example",
      "large class"
    ],
    "note": {
      "typesetting": "TeX",
      "pages": 0,
      "language": "en",
      "license": "arXiv",
      "status": "editable"
    }
  }
}